Summarizing information from different sources based on personal learning styles

ABSTRACT

A method, computer system, and a computer program product for summarizing a piece of information based on a personal learning style of a user is provided. The present invention may include summarizing to the piece of information associated with at least one information source, wherein an output is generated from the summarized piece of information. The present invention may then include generating a summary of the piece of information based on the personal learning style of the user and a plurality of data associated with the user, wherein the personal learning style of the user is determined by a personality test. The present invention may further include presenting the generated summary to the user.

BACKGROUND

The present invention relates generally to the field of computing, andmore particularly to computational linguistics.

When a person is added to a thread of any information or conversationsource, such as an email, web page forum or messaging boards, instantmessaging, and other forms of digital communication medium, the personmay not know about the discussed topic. As such, the person has to readthe entire chain of information to better understand the discussedtopic. Such a process is very time consuming and, in some cases, theperson has to read information multiple times and/or make annotations tofully understand the information. And even after completing this timeconsuming process, the person may still not fully understand theinformation or have a different interpretation of the information or thediscussed topic.

SUMMARY

Embodiments of the present invention disclose a method, computer system,and a computer program product for summarizing a piece of informationbased on a personal learning style of a user. The present invention mayinclude summarizing the piece of information associated with at leastone information source, wherein an output is generated from thesummarized piece of information. The present invention may then includegenerating a summary of the piece of information based on a personallearning style of the user and a plurality of data associated with theuser, wherein the personal learning style of the user is determined by apersonality test. The present invention may further include presentingthe generated summary to the user.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

These and other objects, features and advantages of the presentinvention will become apparent from the following detailed descriptionof illustrative embodiments thereof, which is to be read in connectionwith the accompanying drawings. The various features of the drawings arenot to scale as the illustrations are for clarity in facilitating oneskilled in the art in understanding the invention in conjunction withthe detailed description. In the drawings:

FIG. 1 illustrates a networked computer environment according to atleast one embodiment;

FIG. 2 is an operational flowchart illustrating a process for cognitiveinformation summarization according to at least one embodiment;

FIG. 3 is an operational flowchart illustrating a process for cognitivepersonal learning style determination according to at least oneembodiment;

FIG. 4 is a block diagram of internal and external components ofcomputers and servers depicted in FIG. 1 according to at least oneembodiment;

FIG. 5 is a block diagram of an illustrative cloud computing environmentincluding the computer system depicted in FIG. 1, in accordance with anembodiment of the present disclosure; and

FIG. 6 is a block diagram of functional layers of the illustrative cloudcomputing environment of FIG. 5, in accordance with an embodiment of thepresent disclosure.

DETAILED DESCRIPTION

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. This invention may, however, be embodied inmany different forms and should not be construed as limited to theexemplary embodiments set forth herein. Rather, these exemplaryembodiments are provided so that this disclosure will be thorough andcomplete and will fully convey the scope of this invention to thoseskilled in the art. In the description, details of well-known featuresand techniques may be omitted to avoid unnecessarily obscuring thepresented embodiments.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language, Python programminglanguage or similar programming languages. The computer readable programinstructions may execute entirely on the user's computer, partly on theuser's computer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider). In some embodiments,electronic circuitry including, for example, programmable logiccircuitry, field-programmable gate arrays (FPGA), or programmable logicarrays (PLA) may execute the computer readable program instructions byutilizing state information of the computer readable programinstructions to personalize the electronic circuitry, in order toperform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The following described exemplary embodiments provide a system, methodand program product for summarizing a piece of information based on thepersonal learning style of a user. As such, the present embodiment hasthe capacity to improve the technical field of computational linguisticsby analyzing and summarizing at least one piece of information from atleast one information source, and then generating an information summarybased on the personal learning style of the user and the data associatedwith the user on the user profile. More specifically, the cognitiveinformation summary program may identify the user, and then determinewhether a personality test is necessary to determine the personallearning style of the user. The cognitive information summary programmay then receive at least one information source from the user, whichthe cognitive information summary program utilizes at least oneapplication program interface (API) to analyze and summarize. Thesummarizing of the piece of information includes the most used words bythe user and any other important data included in the user profileassociated with the identified user. The analyzed and summarized pieceof information may then be converted into a form of information summarybased on the personal learning style of the user. The cognitiveinformation summary program may then present the information summary tothe user. The cognitive information summary program may then requestfeedback from the user to learn the effectiveness of the summary.

As previously described, when a person is added to a thread of anyinformation or conversation source, such as an email, web page forum ormessaging boards, instant messaging, and other forms of digitalcommunication medium, the person may not know about the discussed topic.As such, the person has to read the entire chain of information tobetter understand the discussed topic. Such a process is very timeconsuming and, in some cases, the person has to read informationmultiple times and/or make annotations to fully understand theinformation. And even after completing this time consuming process, theperson may still not fully understand the information or have adifferent interpretation of the information or the discussed topic.

As such, in many cases, reading the chain of information does not leadto a complete or even better understanding of the discussed topic, sinceeach person possess different learning styles or characteristics tolearn and comprehend information. A majority of people are categorizedas visual learners (i.e., people who learn better with images, videos orsome form of visual stimuli), auditory learners (i.e., people who learnbetter with audio files and recordings or some form of auditorystimuli), or kinesthetic learners (i.e., people who learn better whenfocused on emotions or feelings).

Therefore, it may be advantageous to, among other things, summarize thethread of any information and/or conversation, such as an email, webpage forum or messaging boards, instant messaging, and other forms ofdigital communication medium, and provide a summary based on thepersonal learning style of the user (e.g., Neuro-Linguistic ProgrammingPersonality Types (NLP), which may include visual, auditory andkinesthetic types as NLP types). As such, based on a user's personallearning type (e.g., NLP type), the output of information may be in aform (e.g., auditory records, images, videos) that the user may be ableto better comprehend in order to extrapolate the necessary informationfrom the thread. Therefore, it may be easier for the user to understanda topic and may reduce the time of reading and/or responding to a threadof information.

According to at least one embodiment, the cognitive information summaryprogram may send a brief personality test to a user. The cognitiveinformation summary program may utilize different learning styleassessment tests (i.e., personality tests). The answers to the briefpersonality test provided by the user may then be utilized to determinethe personal learning type (e.g., NLP type) of the user.

According to at least one embodiment, the cognitive information summaryprogram may receive, as inputs, by the user, results from a recentpersonality test, at least one thread of information, and words mostused by a person in the thread of information and/or the user. Thecognitive information summary program may then summarize the at leastone thread of information and provide, as an output, an informationsummary (i.e., a summary) based on the type of person, or personallearning style (e.g., NLP type) of the user (i.e., based on the resultsof the personality test).

According to at least one embodiment, the cognitive information summaryprogram may identify the most used words (e.g., phrases, terms,individual nouns or verbs) by the person throughout the thread ofinformation. The cognitive information summary program may then utilizethe most used words in the summary. The present embodiment may includeutilizing the most used words (e.g., phrases, terms, individual nouns orverbs) by the user based on previous threads of information.

In the present embodiment, the user may have the option of changing thetype of personal learning style, or the way of presenting the summary atany time. For example, if the user is receiving auditory recordings tosummarize information and the user decides that images would be morehelpful for a particular thread of information, then the user may changethe summary to generate images or visual summaries of the thread ofinformation rather than auditory recordings.

According to at least one embodiment, the user may give feedback (e.g.,provide a score) for the cognitive information summary program after theuser receives the summary. The feedback (i.e., user feedback) may bebased on whether the user possesses a better understanding of thediscussed topic after receiving and utilizing the summary generated bythe cognitive information summary program. Based on the user feedbackand the historical data of the previous summary, the cognitiveinformation summary program may improve summaries provided to the userin the future.

According to at least one embodiment, the cognitive information summaryprogram may be utilized to summarize information from a book, magazineor any information source in a digital file format. Rather than readinga book, for example, the cognitive information summary program mayconvert the digital file into a summary based on the personal learningstyle of the user. The cognitive information summary program may firstconvert the file into the best form of summary based on the personallearning style of the user. For analysis, the input (i.e., digital file)may be in an understandable or base language or text. For example, whenthe input is audio, then the cognitive information summary program mayutilize a speech-to-text engine (e.g., IBM Watson® Speech to Text (IBMWatson and all IBM Watson-based trademarks and logos are trademarks orregistered trademarks of International Business Machines Corporationand/or its affiliates)) to convert the information into text. Inaddition, the cognitive information summary program may combine theoutput from the speech-to-text engine with an image recognition engine(e.g., IBM Watson® Visual Recognition (IBM Watson and all IBMWatson-based trademarks and logos are trademarks or registeredtrademarks of International Business Machines Corporation and/or itsaffiliates)) to convert the information into images or visualrepresentations.

Referring to FIG. 1, an exemplary networked computer environment 100 inaccordance with one embodiment is depicted. The networked computerenvironment 100 may include a computer 102 with a processor 104 and adata storage device 106 that is enabled to run a software program 108and a cognitive information summary program 110 a. The networkedcomputer environment 100 may also include a server 112 that is enabledto run a cognitive information summary program 110 b that may interactwith a database 114 and a communication network 116. The networkedcomputer environment 100 may include a plurality of computers 102 andservers 112, only one of which is shown. The communication network 116may include various types of communication networks, such as a wide areanetwork (WAN), local area network (LAN), a telecommunication network, awireless network, a public switched network and/or a satellite network.It should be appreciated that FIG. 1 provides only an illustration ofone implementation and does not imply any limitations with regard to theenvironments in which different embodiments may be implemented. Manymodifications to the depicted environments may be made based on designand implementation requirements.

The client computer 102 may communicate with the server computer 112 viathe communications network 116. The communications network 116 mayinclude connections, such as wire, wireless communication links, orfiber optic cables. As will be discussed with reference to FIG. 4,server computer 112 may include internal components 902 a and externalcomponents 904 a, respectively, and client computer 102 may includeinternal components 902 b and external components 904 b, respectively.Server computer 112 may also operate in a cloud computing service model,such as Software as a Service (SaaS), Analytics as a Service (AaaS),Platform as a Service (PaaS), or Infrastructure as a Service (IaaS).Server 112 may also be located in a cloud computing deployment model,such as a private cloud, community cloud, public cloud, or hybrid cloud.Client computer 102 may be, for example, a mobile device, a telephone, apersonal digital assistant, a netbook, a laptop computer, a tabletcomputer, a desktop computer, or any type of computing devices capableof running a program, accessing a network, and accessing a database 114.According to various implementations of the present embodiment, thecognitive information summary program 110 a, 110 b may interact with adatabase 114 that may be embedded in various storage devices, such as,but not limited to a computer/mobile device 102, a networked server 112,or a cloud storage service.

According to the present embodiment, a user using a client computer 102or a server computer 112 may use the cognitive information summaryprogram 110 a, 110 b (respectively) to generate a cognitive informationsummary based on the personal learning style of a user. The cognitiveinformation summary method is explained in more detail below withrespect to FIGS. 2 and 3.

Referring now to FIG. 2, an operational flowchart illustrating theexemplary cognitive information summary process 200 used by thecognitive information summary program 110 a, 110 b according to at leastone embodiment is depicted.

At 202, a user is identified. The cognitive information summary program110 a, 110 b may identify the user by prompting the user (e.g., viadialog box) to provide the user name and password associated with theuser. The dialog box, for example, may include a label “Username” with ablank comment box to the right, and a label “Password” with a blankcomment box to the right. Once the user enters the user name andpassword associated with the user, the user may select the “Submit”button located at the bottom of the dialog box. Each user name andpassword may be associated with a user profile (i.e., personal profile),which is stored on a profile database (e.g., database 114) associatedwith the cognitive information summary program 110 a, 110 b.

If, however, the user is first-time user, then, according to at leastone implementation, the user, for example, may click the “First-TimeUser” button located to the left of the “Submit” button in the dialogbox. The user may then be prompted (e.g., via dialog box) to create auser profile with personal characteristics of the user (e.g., full name,preferred name, email address, age, gender, preferences). Once the userfinishes setting up the user profile, then the user may click the“Finish” button located on the bottom of the dialog box. The createduser profile may then be stored on the profile database.

In the present embodiment, if the user is a first-time user, then thecognitive information summary program 110 a, 110 b may transmit, viacommunication network 116, a brief personality test to the user. Thecognitive information summary program 110 a, 110 b may utilize differentlearning style assessment tests (i.e., personality tests), such as aforced-choice personality test (e.g., Riso-Hudson Enneagram Typeindicator (RHETI)), Grasha-Riechmann Student Learning Style Scales,Paragon Learning Style, Kolb's Learning Style Inventory (LSI)questionnaires, a Visual Aural Read-Write and Kinesthetic (VARK)learning style questionnaire, Jackson's Learning Styles Profiler (LSP),various online learning style quizzes, and another standard personalitytest. Based on the answers provided by the user, the cognitiveinformation summary program 110 a, 110 b may determine the personallearning style of the user. The results of the personality test and thedetermined personal learning style of the user may be saved under theapplicable user name and password, and stored in the profile database. Adetailed operational flowchart of the personal learning styledetermination process 300 in the cognitive information summary program110 a, 110 b will be described in greater detail below with respect toFIG. 3.

In the present embodiment, if the user is a return user, then thecognitive information summary program 110 a, 110 b may retrieve thepersonal learning style of the user from the user profile. If, however,the cognitive information summary program 110 a, 110 b, according to atleast one implementation, determines that there is an error ordiscrepancy with the personal learning style of the user and the actionsof the user (e.g., user feedback, user skips videos generated by thecognitive information summary program 110 a, 110 b) that may affect theaccuracy of the personal learning style determined by the cognitiveinformation summary program 110 a, 110 b, then the cognitive informationsummary program 110 a, 110 b may commence the personal learning styledetermination process 300 as described in greater detail below withrespect to FIG. 3 by prompting the user to respond to a personality testand re-evaluate the previously determined personal learning styleassociated with the user. Since the user's personal learning style maybe a merger or combination of multiple personal learning styles,re-evaluating the previously determined personal learning style of theuser may improve the accuracy of the cognitive information summaryprogram 110 a, 110 b.

In at least one embodiment, the cognitive information summary program110 a, 110 b may periodically prompt the return user to respond to apersonality test and re-evaluate or confirm the previously determinedpersonal learning style associated with the user. In another embodiment,the user may request a new personality test at any time, therebyprompting the cognitive information summary program 110 a, 110 b toproceed with the personal learning style determination process 300 asdescribed in greater detail below with respect to FIG. 3. By clickingthe “New Personality Test” button, for example, located on the bottom ofthe main screen, the user may request a new personality test.

Additionally, each time that the user logs into the cognitiveinformation summary program 110 a, 110 b with the same user name anygenerated data (e.g., user historic data, key words, irrelevant words,personality test results, personal learning style, previous useractions) may be saved on the profile database of the cognitiveinformation summary program 110 a, 110 b. Additionally, the user profilemay be created, modified or updated by the user or service providers.

For example, the user is a return user. Therefore, the user enters theuser's user name “RUGBYQA1782,” associated password, and clicks the“Submit” button. The cognitive information summary program 110 a, 110 bthen retrieves the user profile associated with “RUGBYQA1782.” Thecognitive information summary program 110 a, 110 b determines that a newpersonality test is unnecessary at this time for the user.

In another embodiment, the user may be identified once the cognitiveinformation summary program 110 a, 110 b is loaded on a user device.Once the user opens the main screen for the cognitive informationsummary program 110 a, 110 b, the user may be prompted (e.g., via dialogbox) to confirm the identification of the user. The user's user name ispresented at the top of the dialog box, with “Yes” or “No” buttonsunderneath. If the user's user name matches the user name presented inthe dialog box, the user may select the “Yes” button and the cognitiveinformation summary program 110 a, 110 b retrieves the user profileassociated with the identified user. If, however, the user name did notmatch the user's user name, then the user may click the “No” button inwhich another dialog box may appear for the user to include the user'suser name for the cognitive information summary program 110 a, 110 b toretrieve the correct user profile associated with the user.

In the present embodiment, the cognitive information summary program 110a, 110 b may include any new personality test results in the userprofile stored on the profile database. In at least one embodiment, thenew personality test results are merely listed in the user profile andonly the newest personality test results may be utilized to determinethe personal learning style of the user. In another embodiment, the newpersonality test results are calculated into, or factored into theprevious personality test results to determine the personal learningstyle associated with the user.

Next, at 204, at least one information source is received. Using asoftware program 108 on the user device (e.g., user's computer 102), thecognitive information summary program 110 a, 110 b may receive, as aninput, at least one information source via communication network 116.The received at least one information source may include articles,publications, magazines, books, emails (e.g., a thread of multipleemails), daily user's tasks, instant messaging, short message service(SMS), social media posts (e.g., a thread of multiple comments relatedto one or a series of social media posts) multimedia message service(MMS), web page forums or messaging boards, videos and other forms ofcommunication in digital file format. The digital file format associatedwith the received at least one information source may be uploaded froman information database (e.g., database 114), from a website, or theuser device. Alternatively, the user may manually enter the at least oneinformation source into the cognitive information summary program 110 a,110 b.

Continuing the previous example, RUGBYQA1782 transmits a series of emailrelated to a current employment assignment, approximately 15 pages long,into the cognitive information summary program 110 a, 110 b. The seriesof emails include an ongoing conversation between 10 different employeesin four different departments related to the details of the workassignment. The earliest email was received three days ago and thenewest email was 30 minutes prior to RUGBYQA1782 noticing the series ofemails. Today is RUGBYQA1782's first day returning to work after atwo-week vacation, where RUGBYQA1782 had very limited email access.

Then, at 206, information from the information source is analyzed.Utilizing an application program interface (API), the cognitiveinformation summary program 110 a, 110 b may analyze and summarize thereceived information source. The API may identify the topic discussed inthe information source, extract relevant information from theinformation source, discard any irrelevant information, and identify anyrepetitive sentences, terms, phrases or key words. The cognitiveinformation summary program 110 a, 110 b may utilize several differenttypes of APIs, such as an API that transcribes audio files into writtentext files (e.g., IBM Watson® Speech to Text), an API that transformswritten text files into audio files (e.g., IBM Watson® Text to Speech(IBM Watson and all IBM Watson-based trademarks and logos are trademarksor registered trademarks of International Business Machines Corporationand/or its affiliates)), an API that tags, classifies and searchesvisual content using machine learning (e.g., IBM Watson® VisualRecognition), an API that predicts personality characteristics, needsand values through written text (e.g., IBM Watson® Personality Insights(IBM Watson and all IBM Watson-based trademarks and logos are trademarksor registered trademarks of International Business Machines Corporationand/or its affiliates)), and an API that detects emotional and languagetones in written text (e.g., IBM Watson® Tone Analyzer (IBM Watson andall IBM Watson-based trademarks and logos are trademarks or registeredtrademarks of International Business Machines Corporation and/or itsaffiliates)).

Additionally, the API may search, or provide the cognitive informationsummary program 110 a, 110 b with a software program 108 to search, theinformation database for information already stored on the identifiedtopic (i.e., topic discussed). The previously stored information on theidentified topic may be compared with the recent information received,and suggestions may be provided on additional pieces of information tobe included with the recent information received. In at least oneembodiment, the API may search, or provide the cognitive informationsummary program 110 a, 110 b with a software program 108 to search, theinternet for additional pieces of information to add context to therecent information received. In another embodiment, the API may search,or provide the cognitive information summary program 110 a, 110 b with asoftware program 108 to search, information in the user profileassociated with user for additional pieces of information associatedwith the recent information received on the identified topic. If theuser previously input information related to the recent informationreceived, then the previously input information may be utilized to addcontext to the recent information received. For example, if theinformation source includes a thread of instant messages from the user'srelatives in regards to who has a recipe for chocolate chip cookies, andthe user previously engaged in several of text messages with a cousinwho stated that their uncle bakes the best chocolate chip cookies, thenthe API may use that previous series of text messages to add a commentthat their uncle was previously credited with baking the best chocolatechip cookies.

As an output of the APIs (i.e., output of the APIs may be generated bythe software program(s) 108 provided by the APIs to perform a specificfunction or task, or by the APIs directly), the cognitive informationsummary program 110 a, 110 b may receive a list of key words, repetitivewords or sentences, summary suggestions based on the preferences of theuser (i.e., user preferences), and/or insights associated with theidentified topic. The user preferences may include the type ofpersonality (e.g., auditory, visual, kinesthetic) that the user maychange at the discretion of the user, or may be combined with one ormore types of personality based on the results from the recent and/orprevious personality test results. In some embodiments, the list of keywords may include references to the location (i.e., pointers) of eachkey word in the received information source.

In some embodiments, the repetitive words or sentences may be sortedbased on the preferences of the user (e.g., sorted in a list fromhighest to lowest frequency, sorted in a list from lowest to highestfrequency). In at least one embodiment, the repetitive words orsentences may be presented with a percentage of usage. In the presentembodiment, the user may include as a preference to exclude anyrepetitive words or sentences that are below a certain frequency number(e.g., any repetitive words or sentences with a frequency number below10% are excluded from the list).

In some embodiments, the summary suggestions provided by the API may bebased on the personal learning style of the user as indicated in theuser profile associated with the user. For example, if the user prefersinformation in a visual medium since the user is a visual learner, thenthe API may include suggestions on images related to the relevant words.In some embodiments, the API may also create an affinity diagramsegregating by topic and ordering the images with the appropriatesentences to add context to the images. Then, the information, with thecorresponding images, may be presented in a summary chart (i.e., a briefsummary of the information which may be utilized by the cognitiveinformation summary program 110 a, 110 b to generate an informationsummary based on the personal learning styles of the user). An exampleof a summary chart is provided below.

In some embodiments, the cognitive information summary program 110 a,110 b may determine the words most used by the user based on thehistorical data associated with the identified user in the user profile,and may use these most used words in the summary of the analyzedinformation. The cognitive information summary program 110 a, 110 b maydetermine the most used words of the user by reviewing a history ofmultiple information sources (e.g., emails, social messaging boards,instant messaging), as well as any information from the user profile.For example, if the user is an engineer, the cognitive informationsummary program 110 a, 110 b may utilize more technical words associatedwith the specific discipline of engineering that the user is involvedin.

In some embodiments, the cognitive information summary program 110 a,110 b may also, based on the privacy settings of the user, have accessto any company profile associated with the user, social media profiles,any other profiles associated with the user, and information pertainingto the user's employer, profession and/or occupation, one or more emailaccounts associated with the user, and employer related chats and/orinstant messaging services. For the cognitive information summaryprogram 110 a, 110 b to gain any access to any company profileassociated with the user, social media profiles, any other profilesassociated with the user, information pertaining to the user's employer,profession and/or occupation, one or more email accounts associated withthe user, and employer related chats and/or instant messaging services,the user may have to affirmatively allow the cognitive informationsummary program 110 a, 110 b to access such information. If the userfails to respond to a prompt (e.g., via dialog box) requesting suchaccess, or blocks (i.e., denies) such access (i.e., the user may denyall or some access to specific profiles, email accounts, chat and/orinstant messaging services, or information associated with the userand/or user's employer), then the cognitive information summary program110 a, 110 b may be prohibited to access to such information, emailaccounts, profiles or chat and/or instant messaging services.Additionally, the user may revoke, modify or allow access at any time,and the cognitive information summary program 110 a, 110 b may, inreal-time, prompt (e.g., via dialog box) the user when the cognitiveinformation summary program 110 a, 110 b is about to access specificprofiles, email accounts, chat and/or instant messaging services, orinformation associated with the user and/or user's employer, even if theuser already granted access to such specific profiles, email accounts,chat and/or instant messaging services, or information associated withthe user and/or user's employer. The user may then revoke, modify, orchange the user privacy settings associated with the access by, forexample, selecting the “Modify” button located in the dialog box. Thecognitive information summary program 110 a, 110 b may then pause orsuspend any access to specific profiles, email accounts, chat and/orinstant messaging services, or information associated with the useruntil the user has completed the modification, confirmed that themodification is accurate and effective immediately, and the dialog boxhas disappeared.

In at least one embodiment, if the information associated with the firstuser includes information associated with second user and/or employer,the cognitive information summary program 110 a, 110 b may have toreceive affirmative permission from the second user and/or employer toaccess such information. Failure to receive such affirmative permissionfrom the second user and/or employer may prohibit the cognitiveinformation summary program 110 a, 110 b from accessing any informationrelated to the second user and/or employer. If, however, the first useraffirmatively allows access to such information and the second userdeclines such access, the cognitive information summary program 110 a,110 b may access information only associated with the first user andblock access to any information related to the second user. Thecognitive information summary program 110 a, 110 b may then prompt(e.g., via dialog box) the first user as to whether the cognitiveinformation summary program 110 a, 110 b may proceed with the access ofallowed portions of the information, if the second user has declinedaccess. The first user may then confirm that the cognitive informationsummary program 110 a, 110 b should proceed with access (although suchaccess only relates to the information associated with the first user)or deny such access altogether.

In some embodiments, the cognitive information summary program 110 a,110 b may utilize an extraction engine to extract key words from thetext associated with the information from the at least one informationsource.

In one embodiment, depending on the analyzed information, the summarychart and/or list may be divided into multiple boxes or categories(e.g., understanding the problem or key topic discussed, necessaryactions for a solution and root cause and lessons learned, anyassociated audio recordings, videos, games or images corresponding withany of the boxes or categories). For example, if the thread of emails isrelated to the inclusion of an improper label for a product, then thesummary chart and/or list is as follows:

Subject 1: Understand the Problem

The label printed with the wrong compliance requirements and missing oneP label to be read with a scanner in Storage. The brands and productsaffected are Storage and Power.

Subject 2: Necessary Actions for a Solution

Label was reworked by Employee A to include the appropriate marks on thelabel according to the compliance requirements.

Subject 3: Root Cause and Lessons Learned

Development picked up the Product Number (PN) without reviewing thecompliance requirements and the equipment needed at Storage to use thisPN.

For the above summary chart/list, if the user was a visual learner, thenthe cognitive information summary program 110 a, 110 b may include apicture of the improper label with a red “X” next to that improperlabel, and a picture of the proper or corrected label with a greencheckmark next to the proper label. In addition, a flowchart with theprocess followed that lead to the creation of the improper labelindicating the root cause of the labelling error, and a new flowchartwith the process that will be followed in order to avoid such alabelling error in the future may be depicted.

Continuing the previous example, the cognitive information summaryprogram 110 a, 110 b utilizes three APIs, the IBM Watson® Tone Analyzer,the IBM Watson® Text to Speech and the IBM Watson® Visual Recognition,to analyze and summarize the series of emails. The IBM Watson® ToneAnalyzer is utilized to analyze the different tones used by each of thesenders, the IBM Watson® Text to Speech is utilized to analyze the textand translate the text into an audio recording and the IBM Watson®Visual Recognition is utilized to analyze the various photographs of thedifferent products and brands included in the emails. The APIs generatethe following output:

Identified Topic:

New Work Assignment to evaluate the success of the top 2 brands ofwidgets manufactured by employer for an upcoming sales meeting.

List of Key Words:

Brand A, Brand B.

Repetitive Words or Sentences:

Brand A (45%), Brand B (25%), Brand C (5%), Brand D (5%), Brand E (3%).

Brand A recently had a steep decline in sales (31%), Brand C recentlyhad an incline in sales due to Valentine's Day (15%), Brand D was verypopular among a younger demographic in the summer months (10%), Brand Bhas always been a top seller (5%).

Summary Suggestions:

Provide sales history on the brands, including if the sales of eachbrand is consistent or fluctuates over a calendar year.

Insights:

A recent email (in a separate thread of emails) with the reported salesof each brand of widgets manufactured by the employer during the pastcalendar year; another email (in a separate thread of emails) with theprojected sales of each brand of widgets manufactured by the employer inthe upcoming calendar year; recent set of advertisements on social mediafor a competitor company's widgets that are similar to Brand E thatrecently has more than 800,000 views and 300,000 likes or shares.

Since RUGBYQA1782 is a part of the accounting and sales department,RUGBYQA1782's preferences include providing historical data associatedwith the sales of the brands to determine the top two brands of widget.

Then, at 208, the information is converted based on the personallearning style of the user. Utilizing a converter, the analyzedinformation and generated output (e.g., list of key words, repetitivewords or sentences, summary suggestions based on user preferences,insights associated with the identified topic) may be converted into aninformation summary (i.e., summary) based on the personal learning styleof the user. The personal learning style of the user (e.g.,neuro-linguistic personality (NLP) type) may be based on the results ofthe most recent, or combination of a series of, personality tests takenby the user. A detailed operational flowchart of the personal learningstyle determination process 300 in the cognitive information summaryprogram 110 a, 110 b will be described in greater detail below withrespect to FIG. 3.

The cognitive information summary program 110 a, 110 b may utilizeseveral different types of converters, as such as a high speechconverter to transcribe audio files into written text files (e.g., IBMWatson® Speech to Text), a high speech converter to transform writtentext files into audio files (e.g., IBM Watson® Text to Speech), aconverter that tags, classifies and searches visual content usingmachine learning (e.g., IBM Watson® Visual Recognition), a convertingservice that predicts personality characteristics, needs and valuesthrough written text (e.g., IBM Watson® Personality Insights), and aconverting service that detects emotional and language tones in writtentext (e.g., IBM Watson® Tone Analyzer). In some embodiments, the APIsutilized to analyze the information from the received source ofinformation may also be utilized as the converter.

In the present embodiment, the cognitive information summary program 110a, 110 b may retrieve the personal learning style of the user from theuser profile stored in the profile database, which may include, amongother data associated with the user, the personal learning style of theuser. Once the personal learning style of the user is retrieved, thecognitive information summary program 110 a, 110 b may transmit the dataassociated with the personal learning style of the user to the convertervia communication network 116. The converter may then utilize the datatransmitted on the personal learning style of the user to the determinethe form (e.g., images, videos, games, audio recordings) of the summaryto be presented to the user.

In the present embodiment, the converter may utilize the outputgenerated by the APIs (e.g., list of key words, repetitive words orsentences, summary suggestions based on user preferences, insightsassociated with the identified topic) to determine the context of theinformation summary. The summary suggestions may provide the generalcontext (i.e., frame or information related to main idea/identifiedtopic) that should be included in the information summary. The summarysuggestions may also provide possible images or videos that may beincluded in the information summary depending on the personal learningstyle of the user. For example, the summary suggestions will include aproper label and an improper label of the same product, if theidentified topic of the information is identifying issues with productlabeling. The converter may also utilize the output including the listof key words and repetitive words or sentences to incorporate the sameterminology or images into the information summary. Based on the rank(e.g., the percentage of usage) of the repetitive words or sentences,the converter may include higher ranked (e.g., words or sentences with ahigher percentage of usage) words or sentences rather than lower ranked(e.g., words or sentences with a lower percentage of usage) words orsentences. If the converter transforms the information into images or avisual summary, then the repetitive words or sentences may be includedwith the appropriate images to provide context for the images. Forexample, if the phrase “improper label” is repetitively associated witha particular label, then the converter will identify that particularlabel as the “improper label.” The converter may utilize the insightsrelated to the identified topic to add context to the summary. Forexample, if several members of the distribution department stated in theinformation provided that the issue is directly related to improperlabeling, then the converter will determine that improper labeling is animportant part of the summary and therefore, images or text related toimproper labeling should be included in the information summary.

In the present embodiment, the converter may utilize the outputgenerated by the APIs to determine whether any images, diagrams or otherform of visual representation is important to the identified topic andmay be included in the information summary. If, based on the summarysuggestions, list of key words or repetitive sentences, identifiedtopic, or insights related to the identified topic the visualrepresentation is identified as irrelevant, then the visualrepresentation may be considered unimportant and excluded from theinformation summary. In at least one embodiment, any visualrepresentation (e.g., image, table, chart or diagram) included in theinformation may be included in the information summary. If the visualrepresentation is considered unimportant or irrelevant based on theoutput generated by the APIs, then the converter may include a link (forvisual and kinesthetic learners) or a separate audio file (for auditorylearners) labeled as, for example, “Additional Information,” to includesuch visual representation in visual or audio format depending on thepersonal learning style of the user.

In at least one embodiment, if the user is a visual learner and novisual representations were provided in the information or no visualrepresentations were identified as relevant in the information, then theconverter may retrieve related images from a database or internet togenerate the visual summary for the user. For example, if the summary isrelated to including the wrong product number on a label, then thevisual summary will include a first box with the improper productnumber. On top of the first box, the converter includes a red “X,” and asecond box with the proper product number. On top of the second box, theconverter includes a green check mark. Therefore, the convertertransforms the written text on improper labeling with a visualrepresentation identifying the mislabeling issue as including the wrongproduct number in the label, and utilize the boxes and the red “X” andgreen check mark to distinguish the wrong product number and the correctproduct number.

In at least one embodiment, if the user is an auditory learner, then theconverter may convert a summary of the written text generated by theoutput of the APIs into an audio file or recording. For example, theaudio file will simply state, “the identified topic is the improperlabeling of Product XYZ. At some point, the wrong product number of123456 was included on the label related to Product XYZ instead of thecorrect product number 654321.” If any visual representations areincluded in the information that user is able to access (i.e., dependingwhether the visual representation is included as a separate audio fileor excluded from conversion since the visual representation wasidentified as irrelevant), then the converter may transform the visualrepresentation into an audio recording. The audio recording may describethe visual representation and may identify the source from which thevisual representation is derived from. For example, if a visualrepresentation of the improper label was included in the information,then the converter will translate a description of the improper labelinto an audio recording, stating, “The top right side of the labelincludes Product Name XYZ and the top left side of the label includesSerial Number 56GH56IKZ . . . ”

Continuing the previous example, the cognitive information summaryprogram 110 a, 110 b previously determined that RUGBYQA1782 is akinesthetic learner based on the NLP personality type. As such,RUGBYQA1782 comprehends and understands information when presented in aninteractive form of summary, such as a simple interactive game. As such,the cognitive information summary program 110 a, 110 b utilize a highspeed converter that searches the internet for images of Brand A, BrandB, Brand C, Brand D and Brand E. The converter further transforms thesale history of each of the brands into a line graph in which the salerelated to each brand is plotted onto the line graph over the calendaryear, and another line graph for the projected sales of each brand inthe upcoming calendar year.

Then, at 210, a summary is presented. The summary generated by thecognitive information summary program 110 a, 110 b may be presented tothe user, in the form determined to be best for the user based on thepersonal learning style of the user.

In the present embodiment, the user may change the form of the summarypresented. For example, if the presented summary includes images, theuser may prefer an audio based summary when the user is driving andunable to view images at that time. The user may, via virtual assistant,audio-enabled device, or clicking a “Change Summary” button, forexample, located on the bottom of the screen when the summary ispresented, change the form of the summary. The user may be prompted, viadialog box or computer generated voice command, to select a new form ofsummary (e.g., audio, visual or kinesthetic).

Continuing the previous example, the cognitive information summaryprogram 110 a, 110 b displays a visual summary in which RUGBYQA1782connects the discussed brands of widgets with the respective reportedand projected sales as shown on the line graphs generated by theconverter. When RUGBYQA1782 clicks on the respective reported orprojected sales, then additional details on any fluctuations or trendsof the sales history of each brand is outlined. When RUGBYQA1782 hoversover the name of the brand, the comments from the different employeesassociated with each brand are provided. Any brand with additionalinformation pertaining to the popularity of similar widgets fromcompetitors or the brand itself, including recent advertisements orsocial media posts or comments, will be highlighted in yellow. WhenRUGBYQA1782 clicks the name of the brand, another page will appear inwhich RUGBYQA1782 may access the additional videos, images or socialmedia posts related to the brand or similar competing brand. After fiveminutes of reviewing the visual summary, the cognitive informationsummary program 110 a, 110 b prompts RUGBYQA1782 to start a simpleinteractive game with questions related to the visual summary presented.

However, since RUGBYQA1782 is getting dressed for work and unable toperform the simple interactive game at this time, RUGBYQA1782 verballycommands RUGBYQA1782's virtual assistant device to change the summary toaudio. As such, the cognitive information summary program 110 a, 110 bchanges the form of the summary into an audio recording. An image of anaudio player appears on RUGBYQA1782's smart phone, and the audiorecording generated by cognitive information summary program 110 a, 110b plays the summary for RUGBYQA1782.

In another embodiment, the simple interactive game may include a visualsummary of the information, and the cognitive information summaryprogram 110 a, 110 b may include a series of questions. The user mayrespond to each question by, for example, clicking a “Yes” or “No”button and reinforce the information provided. For example, if the userselects the incorrect response, then a red “X” next to that incorrectresponse will be shown, and if the user selects a correct response, thena picture of a green checkmark next to the correct response will beshown. As such, the interactive game generated for a user with akinesthetic personal learning style may include simple questions toreinforce the user's understanding of the information provided, as wellas keep the user engaged in reading and reviewing the informationprovided. For example, the interactive game is a relation game in whichthe cognitive information summary program 110 a, 110 b generates acolumn with the brand images (Column A), and another column with thebrand descriptions in a different order (Column B), and the user has torelate the brand images in Column A with the correct brand descriptionsin Column B. As such, the cognitive information summary program 110 a,110 b may need minimal, if any, programming to provide a simpleinteractive game for the user.

In another embodiment, the summary created for a kinesthetic learner maybe similar to the summary created for a visual learner. The cognitiveinformation summary program 110 a, 110 b may present a visual summary ofthe information, and after a certain period of time, the cognitiveinformation summary program 110 a, 110 b may present questions toreinforce the information presented to the user. In at least oneembodiment, the cognitive information summary program 110 a, 110 b maygive the user five minutes to review the visual summary presented, andthen prompt (e.g., via dialog box) the user to participate in a simpleinteractive game (e.g., respond to a series of questions about theinformation presented). The dialog box, for example, will include “Yes”or “No” buttons for the user to respond to and indicate whether the userwants to participate in the simple interactive game. If the user clicksthe “Yes” button, then the dialog box will disappear and the game willproceed. If, however, the user clicks the “No” button, then the dialogbox will disappear and the visual summary will reappear. In at least oneother embodiment, the default time of five minutes may be re-configuredor changed by an administrator or the user.

In another embodiment, a kinesthetic learner may commence the simpleinteractive game at any time after the visual summary is presented. Theuser may, for example, click on any part of the visual summary, or clickon any key of the mobile device, and the user will be prompted, viadialog box, to participate in the simple interactive game. The dialogbox will include “Yes” or “No” buttons for the user to respond to andindicate whether the user wants to participate in the simple interactivegame. If the user clicks the “Yes” button, then the dialog box willdisappear and the game will proceed. If, however, the user clicks the“No” button, then the dialog box will disappear and the visual summarywill reappear.

Then at 212, user feedback is requested. The user feedback may beutilized by the cognitive information summary program 110 a, 110 b todetermine the effectiveness of the displayed summary. The cognitiveinformation summary program 110 a, 110 b may prompt (e.g., via dialogbox) the user to provide user feedback in which the user may providecomments associated with the usefulness of the cognitive informationsummary program 110 a, 110 b. In some embodiments, the user may providea score (i.e., normalized quantity from 1 to 10) on the effectiveness ofthe cognitive information summary program 110 a, 110 b, as well asprovide comments to further explain the reason for the score given.Based on the user feedback, the cognitive information summary program110 a, 110 b may determine whether the form of the summary, context ofthe summary, or determined personal learning style of the user may bere-evaluated or modified.

In some embodiments, the user may be prompted by at least two forms ofnotification (e.g., visual via dialog box, audio via loud alert, touchvia vibration of the user device) to provide user feedbacksimultaneously to when the summary is displayed at 210. In otherembodiments, the summary may be presented at 210 first and then user maybe prompted to provide user feedback shortly thereafter.

In the present embodiment, the user may opt out of providing userfeedback for a particular summary. When prompted (e.g., via dialog box)to provide user feedback, the user may click, for example, the “Ignore”button located at the bottom of the dialog box. Then, the dialog box maydisappear. In some embodiments, the user may command a virtual assistantor audio enabled device to ignore the user feedback request.

In some embodiments, the cognitive information summary program 110 a,110 b may preclude the user from not providing at least one userfeedback for a certain time period or certain number of displayedsummaries. In at least one embodiment, the default may be three (3)consecutive displayed summaries. As such, if the user fails to provideuser feedback for three consecutive displayed summaries, then the usermay not be provided with the “Ignore” button or option when the nextsummary is displayed. The user may have to provide user feedback forthat summary. In another embodiment, such default may be re-configuredor changed by an administrator or the user.

In at least one embodiment, the user may provide user feedback at anytime. The user may select the “User Feedback” button located at thebottom of the main screen to provide such user feedback. Once the “UserFeedback” button is selected, then the user may be prompted (e.g., viadialog box) to provide, in a comment box, the summary or general issues(e.g., improper personal learning style of the user, misleading contextincluded the summaries) that the user feedback is associated with, andclick the “Submit” button located at the bottom of the dialog box.

Continuing the previous example, while the summary is playing forRUGBYQA1782, the cognitive information summary program 110 a, 110 bprompts RUGBYQA1782 by alerting the user with a loud bleeping sound anddisplaying a dialog box requesting user feedback from RUGBYQA1782. SinceRUGBYQA1782 heard the loud bleeping sound, RUGBYQA1782 is aware thatuser feedback has been requested by the cognitive information summaryprogram 110 a, 110 b. However, due to limited time, RUGBYQA1782 isunable to provide user feedback at this time. Therefore, RUGBYQA1782commands the virtual assistant device to ignore the user feedbackprompt. The user feedback dialog box then disappears from the screen ofthe smart phone.

In at least one embodiment, the cognitive information summary program110 a, 110 b may utilize an extraction engine to search through thereceived source(s) of information, and to extract the most used words(e.g., phrases, terms, individual nouns or verbs) by the person orpeople in the received source(s) of information. The identified mostused words by the person or people in the received source(s) ofinformation may be included in the summary presented to user to furtherexplain the pieces of information included in the received source(s) ofinformation to the user. For example, if the instant messaging chats arebetween three people, the cognitive information summary program 110 a,110 b utilizes the extraction engine to identify “disagreed” and “basedon the recent team meeting last month” as the most used words by two ofthree people included in the received instant messaging chats. Thecognitive information summary program 110 a, 110 b will include“disagreed” and “based on the recent team meeting last month” into thesummary presented to the user.

In another embodiment, if the user is determined to be a visual learner,then the cognitive information summary program 110 a, 110 b may generatea series of images conveying the information from the informationsource. Continuing the previous example, if the user was identified as avisual learner, the cognitive information summary program 110 a, 110 bwill then present a series of flowcharts with images for each of theBrands discussed in the series of emails and a picture of such person,along with their respective title in the company, who stated that thespecific brand is the one of the top two brands manufactured by theemployer. The flowchart may include any supporting documents next to thespecific person that included such supporting documents in the series ofemails, as well as an image for each similar competitor brand identifiedin the email chain. In addition, links with videos or images related toany recent advertisements, social media posts or comments would beincluded in a separate flowchart and categorized with the brand relatedto the video or image.

In another embodiment, if the user is determined to be an auditorylearner, then the cognitive information summary program 110 a, 110 b maygenerate one or more audio files to convey the information from theinformation source. Continuing the previous example, if the user wasidentified as an auditory learner, the cognitive information summaryprogram 110 a, 110 b will then present one audio file in which a summaryof the written text in the series of emails is transcribed into an audiorecording. The user will then be able to listen to the audio file andany videos related to any recent advertisements, social media posts orcomments. In addition, any images, visual representations or documentsincluded in the series of emails or in any recent advertisements, socialmedia posts or comments will be described to the user in the audio file.

Referring now to FIG. 3, an operational flowchart illustrating theexemplary cognitive personal learning style determination process 300used by the cognitive information summary program 110 a, 110 b accordingto at least one embodiment is depicted.

At 302, a personality test is transmitted to the user. Utilizing asoftware program 108, the personality test may be transmitted, from atest database (e.g., database 114), to the user via communicationnetwork 116. The personality test may be based on a standard personalitytest (e.g., NLP quiz) that determines the personality type of the userbased on the beliefs, values, and other factors that affect the user'sbehavior, social manners and how the user learns information (i.e.,personal learning style). The cognitive information summary program 110a, 110 b may randomly select the questions included in the personalitytest from the test database. Alternatively, the cognitive informationsummary program 110 a, 110 b may utilize a test engine to selectquestions based on the data associated with the user profile and theidentified user. For example, if the user is a return user and thecognitive information summary program 110 a, 110 b has difficultydetermining whether the personal learning style of the user iskinesthetic or visual, then the test engine may select questionsdesigned to clarify whether the user is kinesthetic or visual.

In some embodiments, the cognitive information summary program 110 a,110 b may provide a maximum number of questions that may be included inthe personality test in order for the personality test to be brief andquick for the user. In at least one embodiment, the default maximumnumber of questions may be nine questions for the personality test. Inanother embodiment, the maximum number of questions may be re-configuredor changed by an administrator or the user.

In some embodiments, the cognitive information summary program 110 a,110 b may include a minimum number of questions that may be included inthe personality test in order for the personality test to be accurateand effective in determining the personal learning style of the user. Inat least one embodiment, the default minimum number of questions may befour questions for the personality test. In another embodiment, theminimum number of questions may be re-configured or changed by anadministrator or the user.

Additionally, the user may be prompted (e.g., via dialog box) by thecognitive information summary program 110 a, 110 b, when the personalitytest is ready for the user to review and provide answers. The dialogbox, for example, may include a statement indicating that the user isrequested to take a personality test, and further asking the userwhether the user is ready to begin with a “Yes” button and “No” buttonlocated at the bottom of the dialog box. If the user clicks the “No”button, then a timer, for example, may appear and the user may promptedthat the user has a certain amount of time to click the “Yes” button.The user may be precluded from opting out of taking the personalitytest. As such, the user may not proceed with the cognitive informationsummary program 110 a, 110 b until the personality test is taken.

In another embodiment, if the user is return user and has previouslytaken the personality test, the user may allowed to postpone taking thepersonality test until the next time that the user starts the cognitiveinformation summary program 110 a, 110 b. As such, the cognitiveinformation summary program 110 a, 110 b may proceed with the cognitiveinformation summary process 200 and postpone the cognitive personallearning style determination process 300.

If, however, the user clicks the “Yes” button located at the button ofthe dialog box, then the dialog box may expand to include thepersonality test. The user may provide answers to the questions (i.e.,user answers) in the personality test within a certain period of time.In some embodiments, the cognitive information summary program 110 a,110 b may allot a default amount of 10 minutes to the user to provideanswers to the questions in the personality test. In at least oneembodiment, the allotted amount of time may be re-configured or changedby an administrator or the user. At the bottom of the expanded dialogbox, for example, there may be a “Submit” button. Once the user clicksthe “Submit” button, then the expanded dialog box may disappear and theuser answers may be transmitted via communication network 116 to thecognitive information summary program 110 a, 110 b.

In another embodiment, the user may generate a paper copy of thepersonality test. As such, the user may utilize a writing instrument(e.g., pen, pencil) to answer the questions in the personality test. Theuser may then manually upload the paper copy of the personality testwith the user answers into the cognitive information summary program 110a, 110 b.

For example, the user, RUGBYQA1782, noticed that the most recentsummaries were interactive games and RUGBYQA1782 experienced difficultyunderstanding and comprehending the information included in thesummaries. As such, RUGBYQA1782 decided to take a new personality test.As such, RUGBYQA1782 clicks the “New Personality Test” button located onthe bottom of the main screen, requesting a new personality test. Thecognitive information summary program 110 a, 110 b then randomly selectsa new personality test for RUGBYQA1782. The cognitive informationsummary program 110 a, 110 b notifies RUGBYQA1782 that the newpersonality test is ready, and asks RUGBYQA1782 to indicate, by clickingthe “Yes” or “No” button located at the bottom of the dialog box,whether RUGBYQA1782 is ready to start. RUGBYQA1782 clicks the “Yes”button and the dialog box immediately expands displaying a newpersonality test that includes seven questions and a timer showing thatRUGBYQA1782 was given 10 minutes to fully respond to the personalitytest. RUGBYQA1782 completes the new personality test within five minutesand clicks the “Submit” button located at the bottom of the expandeddialog box. The expanded dialog box then disappears.

Next, at 304, answers to the personality test are received from theuser. Utilizing a software program 108, the cognitive informationsummary program 110 a, 110 b may receive, as input, the answers to thepersonality test from the user via communication network 116. Thecognitive information summary program 110 a, 110 b may prompt (e.g., viadialog box) the user to confirm that the answers were received.

In another embodiment, if the user manually uploaded user answers via apaper copy into the cognitive information summary program 110 a, 110 b,then, once the upload has been completed, the cognitive informationsummary program 110 a, 110 b may provide a confirmation that the uploadprocess has been completed. For example, the user may be notified (e.g.,via dialog box) stating “Upload Completed. Thank you.”

Continuing the previous example, shortly after RUGBYQA1782 clicked the“Submit” button at the bottom of the expanded dialog box, RUGBYQA1782receives a prompt stating “Your answers have been received! Thank you.”

Then, at 306, the received user answers are analyzed. Utilizing ananalyzer, the cognitive information summary program 110 a, 110 b mayanalyze the received user answers. An analysis of the received useranswers may be provided to the cognitive information summary program 110a, 110 b. Based on the provided analysis, the cognitive informationsummary program 110 a, 110 b may determine the personal learningstyle(s) of the user at 308. The determined personal style(s) of theuser, as well as the results of the personality test, may be saved andstored on the user profile in the profile database.

In the present embodiment, the personal learning styles of the user maybe based on the Neuro-Linguistic Programming (NLP) personality types(i.e., a psychological approach that involves analyzing strategies usedby successful information and applying them to reach a personal goal,and relates to thoughts, language and patterns of behavior learnedthrough experience to specific outcomes). Based on the NLP personalitytypes, the personal learning style(s) of the user may be one of, or acombination of, three main types (e.g., visual, audio or kinesthetic).In another embodiment, one or more other psychological approaches may beutilized to determine the personality type of the user and subsequentlythe personal learning style of the user.

Continuing the previous example, the analyzer examines the answersprovided by RUGBYQA1782 and based on these answers, the cognitiveinformation summary program 110 a, 110 b determines that RUGBYQA1782 ismore of a visual learner than a kinesthetic learner. As such, thecognitive information summary program 110 a, 110 b saves the results ofthe personality test and the new determined personal learning style ofRUGBYQA1782 to RUGBYQA1782's user profile stored on the profiledatabase.

In at least one embodiment, the profile database, test database andinformation database may be three separate databases. In anotherembodiment, the profile database, test database and information databasemay be a part of one database (e.g., database 114) in which the dataassociated with each profile database, test database and informationdatabase may be indexed separately.

In at least one embodiment, the cognitive personal learning styledetermination process 300 may commence simultaneously with the cognitiveinformation summary process 200 once the user is identified at 202. Thecognitive information summary program 110 a, 110 b may, however, suspendthe cognitive information summary process 200 after the information isanalyzed at 206 until the cognitive personal learning styledetermination process 300 has been completed and the personal learningstyle of the user is determined at 308. In another embodiment, thecognitive information summary process 200 and cognitive personallearning style determination process 300 may commence consecutively. Assuch, once the user is identified at 202, then the cognitive informationsummary process 200 may be suspended, until the cognitive personallearning style determination process 300 has been completed. Then, thecognitive information summary process 200 may continue and receive theinformation source at 204.

The functionality of a computer may be improved by the cognitiveinformation summary program 110 a, 110 b because the cognitiveinformation summary program 110 a, 110 b generates information summariesbased on the personal learning style of the user to provide easyhandling of the information and improve the user's comprehension andunderstanding of the information presented and topic discussed in theinformation source. The cognitive information summary program 110 a, 110b further reduces the time of reading and responding to informationprovided to the user. The inclusion of data associated with the user(e.g., a set of historical data, personality test result(s), personallearning style of the user, a full name of the user, at least onepreferred name of the user, at least one email address for the user, atleast one most used word utilized by the user, at least one userpreference), which may be saved and stored on the profile database, maybe utilized to improve the effectiveness of the summary.

It may be appreciated that FIGS. 2 and 3 provide only an illustration ofone embodiment and do not imply any limitations with regard to howdifferent embodiments may be implemented. Many modifications to thedepicted embodiment(s) may be made based on design and implementationrequirements.

FIG. 4 is a block diagram 900 of internal and external components ofcomputers depicted in FIG. 1 in accordance with an illustrativeembodiment of the present invention. It should be appreciated that FIG.4 provides only an illustration of one implementation and does not implyany limitations with regard to the environments in which differentembodiments may be implemented. Many modifications to the depictedenvironments may be made based on design and implementationrequirements.

Data processing system 902, 904 is representative of any electronicdevice capable of executing machine-readable program instructions. Dataprocessing system 902, 904 may be representative of a smart phone, acomputer system, PDA, or other electronic devices. Examples of computingsystems, environments, and/or configurations that may represented bydata processing system 902, 904 include, but are not limited to,personal computer systems, server computer systems, thin clients, thickclients, hand-held or laptop devices, multiprocessor systems,microprocessor-based systems, network PCs, minicomputer systems, anddistributed cloud computing environments that include any of the abovesystems or devices.

User client computer 102 and network server 112 may include respectivesets of internal components 902 a, b and external components 904 a, billustrated in FIG. 4. Each of the sets of internal components 902 a, bincludes one or more processors 906, one or more computer-readable RAMs908 and one or more computer-readable ROMs 910 on one or more buses 912,and one or more operating systems 914 and one or more computer-readabletangible storage devices 916. The one or more operating systems 914, thesoftware program 108 and the cognitive information summary program 110 ain client computer 102, and the cognitive information summary program110 b in network server 112, may be stored on one or morecomputer-readable tangible storage devices 916 for execution by one ormore processors 906 via one or more RAMs 908 (which typically includecache memory). In the embodiment illustrated in FIG. 4, each of thecomputer-readable tangible storage devices 916 is a magnetic diskstorage device of an internal hard drive. Alternatively, each of thecomputer-readable tangible storage devices 916 is a semiconductorstorage device such as ROM 910, EPROM, flash memory or any othercomputer-readable tangible storage device that can store a computerprogram and digital information.

Each set of internal components 902 a, b also includes a R/W drive orinterface 918 to read from and write to one or more portablecomputer-readable tangible storage devices 920 such as a CD-ROM, DVD,memory stick, magnetic tape, magnetic disk, optical disk orsemiconductor storage device. A software program, such as the softwareprogram 108 and the cognitive information summary program 110 a, 110 bcan be stored on one or more of the respective portablecomputer-readable tangible storage devices 920, read via the respectiveR/W drive or interface 918 and loaded into the respective hard drive916.

Each set of internal components 902 a, b may also include networkadapters (or switch port cards) or interfaces 922 such as a TCP/IPadapter cards, wireless wi-fi interface cards, or 3G or 4G wirelessinterface cards or other wired or wireless communication links. Thesoftware program 108 and the cognitive information summary program 110 ain client computer 102 and the cognitive information summary program 110b in network server computer 112 can be downloaded from an externalcomputer (e.g., server) via a network (for example, the Internet, alocal area network or other, wide area network) and respective networkadapters or interfaces 922. From the network adapters (or switch portadaptors) or interfaces 922, the software program 108 and the cognitiveinformation summary program 110 a in client computer 102 and thecognitive information summary program 110 b in network server computer112 are loaded into the respective hard drive 916. The network maycomprise copper wires, optical fibers, wireless transmission, routers,firewalls, switches, gateway computers and/or edge servers.

Each of the sets of external components 904 a, b can include a computerdisplay monitor 924, a keyboard 926, and a computer mouse 928. Externalcomponents 904 a, b can also include touch screens, virtual keyboards,touch pads, pointing devices, and other human interface devices. Each ofthe sets of internal components 902 a, b also includes device drivers930 to interface to computer display monitor 924, keyboard 926 andcomputer mouse 928. The device drivers 930, R/W drive or interface 918and network adapter or interface 922 comprise hardware and software(stored in storage device 916 and/or ROM 910).

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Analytics as a Service (AaaS): the capability provided to the consumeris to use web-based or cloud-based networks (i.e., infrastructure) toaccess an analytics platform. Analytics platforms may include access toanalytics software resources or may include access to relevantdatabases, corpora, servers, operating systems or storage. The consumerdoes not manage or control the underlying web-based or cloud-basedinfrastructure including databases, corpora, servers, operating systemsor storage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 5, illustrative cloud computing environment 1000is depicted. As shown, cloud computing environment 1000 comprises one ormore cloud computing nodes 100 with which local computing devices usedby cloud consumers, such as, for example, personal digital assistant(PDA) or cellular telephone 1000A, desktop computer 1000B, laptopcomputer 1000C, and/or automobile computer system 1000N may communicate.Nodes 100 may communicate with one another. They may be grouped (notshown) physically or virtually, in one or more networks, such asPrivate, Community, Public, or Hybrid clouds as described hereinabove,or a combination thereof. This allows cloud computing environment 1000to offer infrastructure, platforms and/or software as services for whicha cloud consumer does not need to maintain resources on a localcomputing device. It is understood that the types of computing devices1000A-N shown in FIG. 5 are intended to be illustrative only and thatcomputing nodes 100 and cloud computing environment 1000 can communicatewith any type of computerized device over any type of network and/ornetwork addressable connection (e.g., using a web browser).

Referring now to FIG. 6, a set of functional abstraction layers 1100provided by cloud computing environment 1000 is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 6 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 1102 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 1104;RISC (Reduced Instruction Set Computer) architecture based servers 1106;servers 1108; blade servers 1110; storage devices 1112; and networks andnetworking components 1114. In some embodiments, software componentsinclude network application server software 1116 and database software1118.

Virtualization layer 1120 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers1122; virtual storage 1124; virtual networks 1126, including virtualprivate networks; virtual applications and operating systems 1128; andvirtual clients 1130.

In one example, management layer 1132 may provide the functionsdescribed below. Resource provisioning 1134 provides dynamic procurementof computing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 1136provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 1138 provides access to the cloud computing environment forconsumers and system administrators. Service level management 1140provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 1142 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 1144 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 1146; software development and lifecycle management 1148;virtual classroom education delivery 1150; data analytics processing1152; transaction processing 1154; and cognitive information summary1156. A cognitive information summary program 110 a, 110 b provides away to summarize a piece of information based on the personal learningstyle of the user.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A method for summarizing a piece of informationbased on a personal learning style of a user, the method comprising:summarizing the piece of information associated with at least oneinformation source, wherein an output is generated from the summarizedpiece of information; generating a summary of the piece of informationbased on the personal learning style of the user and a plurality of dataassociated with the user, wherein the personal learning style of theuser is determined by a personality test; and presenting the generatedsummary to the user.
 2. The method of claim 1, wherein presenting thegenerated summary to the user, further comprises: providing the userwith an option to change the presented summary.
 3. The method of claim1, further comprising: identifying the user, wherein a user profile isassociated with the user; receiving, from the identified user, the atleast one information source; and analyzing the piece of informationincluded in the at least one information source.
 4. The method of claim1, further comprising: requesting at least one piece of feedback by theuser.
 5. The method of claim 1, wherein generating the summary of thepiece of information based on the personal learning style of the userand the plurality of data associated with the user, wherein the personallearning style of the user is determined by the personality test,further comprises: transmitting, to the user, the personality test,wherein the user responds to the transmitted personality test; receivingthe answers to the transmitted personality test from the user; analyzingthe received answers to the transmitted personality test; determiningthe personal learning style of the user based on the analyzed answers tothe transmitted personality test; and storing the analyzed answers tothe transmitted personality test and the determined personal learningstyle of the user on a user profile associated with the user.
 6. Themethod of claim 1, wherein the output is generated from the summarizedpiece of information, further comprises: identifying at least one topicdiscussed in the at least one information source; extracting a pluralityof relevant information from the at least one information source;discarding a plurality of irrelevant information from the at least oneinformation source; and identifying at least one repetitive sentence, atleast one repetitive term, at least one repetitive phrase, and at leastone key word, wherein the identified at least one repetitive sentence,the identified at least one repetitive term, the identified at least onerepetitive phrase, and the identified at least one key word are sortedwith a corresponding percentage of usage in the at least one informationsource.
 7. The method of claim 1, wherein the generated output from thesummarized piece of information is selected from the group consisting ofat least one of the following: a list of key words from the at least oneinformation source, a list of repetitive sentences, a list of repetitivewords, a list of summary suggestions based on a plurality of userpreferences, and a list of insights associated with at least one topicdiscussed.
 8. The method of claim 3, wherein a user profile isassociated with the user, the plurality of data associated with the useris selected from the group consisting of at least one of the following:a set of historical data, wherein the set of historical data includes atleast one previous personality test result, and the at least onepersonal learning style of the identified user, a full name, at leastone preferred name, at least one email address, at least one most usedword utilized by the identified user, and at least one user preference.9. A computer system for summarizing a piece of information based on apersonal learning style of a user, comprising: one or more processors,one or more computer-readable memories, one or more computer-readabletangible storage medium, and program instructions stored on at least oneof the one or more tangible storage medium for execution by at least oneof the one or more processors via at least one of the one or morememories, wherein the computer system is capable of performing a methodcomprising: summarizing the piece of information associated with atleast one information source, wherein an output is generated from thesummarized piece of information; generating a summary of the piece ofinformation based on the personal learning style of the user and aplurality of data associated with the user, wherein the personallearning style of the user is determined by a personality test; andpresenting the generated summary to the user.
 10. The computer system ofclaim 9, wherein presenting the generated summary to the user, furthercomprises: providing the user with an option to change the presentedsummary.
 11. The computer system of claim 9, further comprising:identifying the user, wherein a user profile is associated with theuser; receiving, from the identified user, the at least one informationsource; and analyzing the piece of information included in the at leastone information source.
 12. The computer system of claim 9, furthercomprising: requesting at least one piece of feedback by the user. 13.The computer system of claim 9, wherein generating the summary of thepiece of information based on the personal learning style of the userand the plurality of data associated with the user, wherein the personallearning style of the user is determined by the personality test,further comprises: transmitting, to the user, the personality test,wherein the user responds to the transmitted personality test; receivingthe answers to the transmitted personality test from the user; analyzingthe received answers to the transmitted personality test; determiningthe personal learning style of the user based on the analyzed answers tothe transmitted personality test; and storing the analyzed answers tothe transmitted personality test and the determined personal learningstyle of the user on a user profile associated with the user.
 14. Thecomputer system of claim 9, wherein the output is generated from thesummarized piece of information, further comprises: identifying at leastone topic discussed in the at least one information source; extracting aplurality of relevant information from the at least one informationsource; discarding a plurality of irrelevant information from the atleast one information source; and identifying at least one repetitivesentence, at least one repetitive term, at least one repetitive phrase,and at least one key word, wherein the identified at least onerepetitive sentence, the identified at least one repetitive term, theidentified at least one repetitive phrase, and the identified at leastone key word are sorted with a corresponding percentage of usage in theat least one information source.
 15. The computer system of claim 9,wherein the generated output from the summarized piece of information isselected from the group consisting of at least one of the following: alist of key words from the at least one information source, a list ofrepetitive sentences, a list of repetitive words, a list of summarysuggestions based on a plurality of user preferences, and a list ofinsights associated with at least one topic discussed.
 16. The computersystem of claim 11, wherein a user profile is associated with the user,the plurality of data associated with the user is selected from thegroup consisting of at least one of the following: a set of historicaldata, wherein the set of historical data includes at least one previouspersonality test result, and the at least one personal learning style ofthe identified user, a full name, at least one preferred name, at leastone email address, at least one most used word utilized by theidentified user, and at least one user preference.
 17. A computerprogram product for summarizing a piece of information based on apersonal learning style of a user, comprising: one or morecomputer-readable storage media and program instructions stored on atleast one of the one or more tangible storage media, the programinstructions executable by a processor to cause the processor to performa method comprising: summarizing the piece of information associatedwith at least one information source, wherein an output is generatedfrom the summarized piece of information; generating a summary of thepiece of information based on the personal learning style of the userand a plurality of data associated with the user, wherein the personallearning style of the user is determined by a personality test; andpresenting the generated summary to the user.
 18. The computer programproduct of claim 17, wherein presenting the generated summary to theuser, further comprises: providing the user with an option to change thepresented summary.
 19. The computer program product of claim 17, furthercomprising: identifying the user, wherein a user profile is associatedwith the user; receiving, from the identified user, the at least oneinformation source; and analyzing the piece of information included inthe at least one information source.
 20. The computer program product ofclaim 17, wherein generating the summary of the piece of informationbased on the personal learning style of the user and the plurality ofdata associated with the user, wherein the personal learning style ofthe user is determined by the personality test, further comprises:transmitting, to the user, the personality test, wherein the userresponds to the transmitted personality test; receiving the answers tothe transmitted personality test from the user; analyzing the receivedanswers to the transmitted personality test; determining the personallearning style of the user based on the analyzed answers to thetransmitted personality test; and storing the analyzed answers to thetransmitted personality test and the determined personal learning styleof the user on a user profile associated with the user.